Generally speaking, sketch-based image retrieval (SBIR) is a technology that aims at matching sketches (e.g., free-hand or hand-drawn sketches) with corresponding images (e.g., photographs or other media captured with an imaging sensor). Current techniques for performing SBIR are inadequate for a number of reasons. Like other types of cross-modal retrieval techniques, SBIR may be implemented, at least to some extent, if the content of the sketches are limited to specific categories of information, and the image retrieval mechanism is pre-trained on those specific categories prior to testing or operating the SBIR system. SBIR retrieval is a much simpler task in this scenario because the visual knowledge of all categories has been explored during the pre-training phase. However, in real-world scenarios, there is no guarantee that the training categories cover all concepts of potential SBIR requests and, in many cases, the SBIR requests can be directed to content that falls outside the categories learned during training. Current SBIR retrieval techniques fail to effectively identify images in these scenarios.